Microsoft Fabric
AI Data Quality: Build a Reliable Foundation
Assess accuracy, completeness, consistency, timeliness, and fitness for purpose before training or deploying an AI system.
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Microsoft Fabric
Assess accuracy, completeness, consistency, timeliness, and fitness for purpose before training or deploying an AI system.
Databricks
An engineer's field note on how data science and engineering roles divide model development, deployment, monitoring, and scale.
AI
An archived beginner Tech Talk using the Titanic dataset, Kaggle, and Azure Machine Learning Studio to introduce classification.
Databricks
An archived introductory Tech Talk covering the Databricks workflow and its place in the nine-part Data Science for Dummies series.
Databricks
An archived Tech Talk showing how the Titanic dataset was prepared and engineered in Databricks before model training.
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